Traffic on different roads often has an impact of the neighbour roads. An accident on one road might cause congestion on the others. Most of the related work capture such interactions as a graph which is pre-computed based on different metrics such as road or euclidean distance between pairwise entities.
Although such methods are easy to implement, they only capture static interactions between entities. In contrast, the interactions among entities are often dynamic and evolve across time.
Figure REF  shows a graph of 6 vertices representing 6 entities, e.g., speed sensors. At 7 AM vertex \(D\)  has strong connections with vertices \(B\)  and \(C\) , while at 9 AM, the connections with vertices \(B\)  and \(C\)  become weaker but vertex \(D\)  has a stronger connection with vertex \(E\)  instead.
However, most of the recent studies fall short on capturing such dynamics [1]}, [2]}, [3]}, [4]}.
